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Efficient Estimation of Agricultural Time Series Models with Nonnormal Dependent Variables

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  • Sukant K. Misra
  • Jeannie Nelson

Abstract

This article proposes using an expanded form of the Johnson S U family as a way to approximate nonnormal distributions in regression models. The distribution is one of the few that allows modeling heteroskedasticity and autocorrelation. The technique is evaluated with Monte Carlo simulation and illustrated through an empirical model of the West Texas cotton basis. Given nonnormality, this technique can substantially reduce the variance of slope parameter estimates relative to least squares procedures. Copyright 2003, Oxford University Press.

Suggested Citation

  • Sukant K. Misra & Jeannie Nelson, 2003. "Efficient Estimation of Agricultural Time Series Models with Nonnormal Dependent Variables," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(4), pages 1029-1040.
    • Handle: RePEc:oup:ajagec:v:85:y:2003:i:4:p:1029-1040
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    File URL: http://hdl.handle.net/10.1111/1467-8276.00505
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    Cited by:

    1. Luter, Ryan L. & Norwood, F. Bailey & Massey, Raymond E., 2004. "Substitutability of Livestock Manure for Chemical Fertilizer: A Contingent Valuation Analysis of Crop Producers," 2004 Annual meeting, August 1-4, Denver, CO 19914, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    2. Sommarat Chantarat & Krirk Pannangpetch & Nattapong Puttanapong & Preesan Rakwatin & Thanasin Tanompongphandh, 2015. "Index-Based Risk Financing and Development of Natural Disaster Insurance Programs in Developing Asian Countries," Risk, Governance and Society, in: Daniel P. Aldrich & Sothea Oum & Yasuyuki Sawada (ed.), Resilience and Recovery in Asian Disasters, edition 127, chapter 0, pages 171-200, Springer.
    3. Gregory Colson & Octavio A. Ramirez & Shengfei Fu, 2014. "Crop Insurance Savings Accounts: A Viable Alternative to Crop Insurance?," Applied Economic Perspectives and Policy, Agricultural and Applied Economics Association, vol. 36(3), pages 527-545.
    4. Qing Sun & Zaiqiang Yang & Xianghong Che & Wei Han & Fangmin Zhang & Fang Xiao, 2018. "Pricing weather index insurance based on artificial controlled experiment: a case study of cold temperature for early rice in Jiangxi, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(1), pages 69-88, March.
    5. Usta, Ilhan & Kantar, Yeliz Mert, 2011. "On the performance of the flexible maximum entropy distributions within partially adaptive estimation," Computational Statistics & Data Analysis, Elsevier, vol. 55(6), pages 2172-2182, June.
    6. Awondo, Sebastain Nde & Datta, Gauri S. & Ramirez, Octavio A. & Fonsah, Esendugue Greg, 2012. "Estimation of crop yield distribution and Insurance Premium using Shrinkage Estimator: A Hierarchical Bayes and Small Area Estimation Approach," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 126778, Agricultural and Applied Economics Association.
    7. Ramirez, Octavio A., 2014. "Appendix I to: Crop Insurance Savings Accounts: A Viable Alternative to Crop Insurance?," Applied Economic Perspectives and Policy Appendices 162318, Agricultural and Applied Economics Association.
    8. Sebastain N. Awondo & Octavio A. Ramirez & Gregory J. Colson & Esendugue G. Fonsah & Genti Kostandini, 2017. "Self†protection from weather risk using improved maize varieties or off†farm income and the propensity for insurance," Agricultural Economics, International Association of Agricultural Economists, vol. 48(1), pages 61-76, January.
    9. Woodard, Joshua D. & Chiu Verteramo, Leslie & Miller, Alyssa P., 2015. "Adaptation of U.S. Agricultural Production to Drought and Climate Change," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205903, Agricultural and Applied Economics Association.
    10. James Mcdonald & Richard Michelfelder & Panayiotis Theodossiou, 2010. "Robust estimation with flexible parametric distributions: estimation of utility stock betas," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 375-387.
    11. Randall A. Lewis & James B. McDonald, 2014. "Partially Adaptive Estimation of the Censored Regression Model," Econometric Reviews, Taylor & Francis Journals, vol. 33(7), pages 732-750, October.
    12. Jason Cook & James McDonald, 2013. "Partially Adaptive Estimation of Interval Censored Regression Models," Computational Economics, Springer;Society for Computational Economics, vol. 42(1), pages 119-131, June.
    13. Ozaki, Vitor & Campos, Rogério, 2017. "Reduzindo a Incerteza no Mercado de Seguros: Uma Abordagem via Informações de Sensoriamento Remoto e Atuária," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 71(4), December.
    14. Sommarat Chantarat, 2015. "Index-based Risk Financing and Development of Natural Disaster Insurance Programs in Developing Countries," PIER Discussion Papers 10., Puey Ungphakorn Institute for Economic Research, revised Nov 2015.
    15. Sommarat Chantarat, 2015. "Index-based Risk Financing and Development of Natural Disaster Insurance Programs in Developing Countries," PIER Discussion Papers 10, Puey Ungphakorn Institute for Economic Research.
    16. Teklewold, Hailemariam & Mekonnen, Alemu, 2020. "Weather at Different Growth Stages, Multiple Climate Smart Practices and Farm Level Risks: Panel Data Evidence from the Nile Basin of Ethiopia," EfD Discussion Paper 20-4, Environment for Development, University of Gothenburg.
    17. Manamba EPAPHRA, 2016. "Determinants of Export Performance in Tanzania," Journal of Economics Library, KSP Journals, vol. 3(3), pages 470-487, September.

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